Learning and Adaptation in Autonomous Robotics Systems

Project Directors

Description

This project is investigating two fundamental types of learning
mechanisms in intelligent robotics systems: an on-line adaptive
component , which allows a system to respond to unexpected situations
and learn while engaged in the problem-solving process; and an
off-line learning component , which allows a system to reason deeply
about its experiences after they have happened, and learn as a result
of its analysis. Adaptation is intended to be fast, similarity-based,
and reactive, while learning will be slower, case-based and
explanation-based, deliberative, and goal-oriented. In other related
work, genetic algorithms are being developed to learn reactive control
parameters.